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    3. Joseph Bloom · Open Source Sparse Autoencoders for all Residual Stream Layers of GPT2-Small
    5. GPT2-Small
    7. Residual Stream
    9. 10-RES-JB
    11. 5061
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    Explanations

    phrases related to winning elections

    oai_token-act-pair · gpt-3.5-turbo

    occurrences of the word "won" and related victory contexts

    oai_token-act-pair · gpt-4o-miniTriggered by @bot
    New Auto-Interp
    Top Features by Cosine Similarity
    Comparing With GPT2-SMALL @ 10-res-jb
    Configuration
    jbloom/GPT2-Small-SAEs-Reformatted/blocks.10.hook_resid_pre
    Prompts (Dashboard)
    24,576 prompts, 128 tokens each
    Dataset (Dashboard)
    Skylion007/openwebtext
    Features
    24,576
    Data Type
    torch.float32
    Hook Point
    blocks.10.hook_resid_pre
    Architecture
    standard
    Context Size
    128
    Dataset
    Skylion007/openwebtext
    Hook Point Layer
    10
    Activation Function
    relu
    Embeds
    IFrame
    Link
    Not in Any Lists

    No Comments

    Negative Logits
     Minotaur
    -0.75
     tatt
    -0.68
     lapse
    -0.66
     Bulg
    -0.65
    senal
    -0.63
    assetsadobe
    -0.63
     derivative
    -0.61
     pros
    -0.60
    IDER
    -0.60
    obyl
    -0.60
    POSITIVE LOGITS
     reelection
    1.25
    elect
    1.15
     majorities
    1.10
     landslide
    1.03
     decisively
    1.02
     elections
    0.99
    election
    0.99
     primaries
    0.96
     landsl
    0.95
     votes
    0.95
    Activations Density 0.101%

    No Known Activations